Replicate data to BigQuery in real time with Datastream

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Before you begin

  1. Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.
  2. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

    Go to project selector

  3. Make sure that billing is enabled for your Cloud project. Learn how to check if billing is enabled on a project.

  4. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

    Go to project selector

  5. Make sure that billing is enabled for your Cloud project. Learn how to check if billing is enabled on a project.

  6. Enable the Datastream API.

    Enable the API

  7. Make sure you have the Datastream Admin role assigned to your user account.

    Go to the IAM page

Requirements

Datastream offers a variety of source options, destination options, and networking connectivity methods.

In this quickstart, we assume that you're replicating data from a Cloud SQL for PostgreSQL database to BigQuery. For the source database, you should be able to configure your database instance to accept connections from Datastream public IP addresses.

Because we can't know the specifics of your environment, we can't provide detailed steps when it comes to your networking configuration.

For this quickstart, you'll select IP allowlisting as the network connectivity method. IP allowlisting is a security feature often used for limiting and controlling access to the data in your source database to trusted users. You can use IP allowlists to create lists of trusted IP addresses or IP ranges from which your users and other Cloud services such as Datastream can access this data. To use IP allowlists, you must open the source Cloud SQL database to incoming connections from Datastream.

Create connection profiles

By creating connection profiles, you're storing some basic information about the source and the destination in Datastream. You can then re-use this information in multiple streams.

In this quickstart, you'll select PostgreSQL as the profile type for your source connection profile, and BigQuery as the profile type for your destination connection profile. Datastream uses the information in the connection profiles to connect to the source database and to BigQuery.

Create a source connection profile for PostgreSQL database

  1. Go to the Connection profiles page for Datastream in the Google Cloud Console.

    Go to the Connection profiles page

  2. Click CREATE PROFILE.

  3. In the Create a connection profile page, click the PostgreSQL profile type (because you want to create a source connection profile for PostgreSQL database).

  4. Supply the following information in the Define connection settings section of the Create PostgreSQL profile page:

    • Enter My Source Connection Profile as the Connection profile name for your source database.
    • Keep the auto-generated Connection profile ID.
    • Select the Region where the connection profile will be stored.

    • Enter Connection details:

      • In the Hostname or IP field, enter a hostname or public IP address that Datastream can use to connect to the source PostgreSQL database. You're providing a public IP address because IP allowlist will be used as the network connectivity method for this quickstart.
      • In the Port field, enter the port number that's reserved for the source database. For a PostgreSQL database, the default port is typically 5432.
      • Enter a Username and Password to authenticate to your source database.
      • In the Database field, enter the name that identifies the database instance. For PostgreSQL databases, this is typically postgres.
  5. In the Define connection settings section, click CONTINUE. The Define connectivity method section of the Create PostgreSQL profile page is active.

  6. Choose the networking method that you'd like to use to establish connectivity between the source database and Datastream. For this quickstart, use the Connectivity method drop-down menu to select IP allowlisting as the networking method.

  7. Configure your source database to allow incoming connections from the Datastream public IP addresses that appear.

  8. In the Define connectivity method section, click CONTINUE. The Test connection profile section of the Create PostgreSQL profile page is active.

  9. Click RUN TEST to verify that the source PostgreSQL database and Datastream can communicate with each other.

  10. Verify that the "Test passed" status appears.

  11. If the test fails, you can address the problem in the appropriate part of the flow, and then return to re-test.

  12. Click CREATE.

Create a destination connection profile for BigQuery

  1. Go to the Connection profiles page for Datastream in the Google Cloud Console.

    Go to the Connection profiles page

  2. Click CREATE PROFILE.

  3. In the Create a connection profile page, click the BigQuery profile type (because you want to create a destination connection profile for BigQuery).

  4. Supply the following information in the Create BigQuery profile page:

    • Enter My Destination Connection Profile as the Connection profile name for your destination BigQuery service.
    • Keep the auto-generated Connection profile ID.
    • Select the Region where the connection profile will be stored.
  5. Click CREATE.

After creating a source connection profile for PostgreSQL database and a destination connection profile for BigQuery, you can use them to create a stream.

Create a stream

In this section, you create a stream to replicate data from a source PostgreSQL database to BigQuery.

Creating a stream includes:

  • Defining settings for the stream.
  • Selecting the connection profile that you created for your source database (the source connection profile). For this quickstart, this is My Source Connection Profile.
  • Configuring information about the source database for the stream by specifying the replication properties, and the tables and schemas in the source database that Datastream:
    • Can transfer into the destination.
    • Is restricted from transferring into the destination.
  • Determining whether Datastream will backfill historical data, as well as stream ongoing changes into the destination, or stream only changes to the data.
  • Selecting the connection profile that you created for BigQuery (the destination connection profile). For this quickstart, this is My Destination Connection Profile.
  • Configuring information about the destination for the stream, such as configuring the BigQuery datasets.
  • Validating the stream.

Define settings for the stream

  1. Go to the Streams page for Datastream in the Google Cloud Console.

    Go to the Streams page

  2. Click CREATE STREAM.

  3. Supply the following information in the Define stream details panel of the Create stream page:

    • Enter My Stream as the Stream name.
    • Keep the auto-generated Stream ID.
    • From the Region menu, select the region where you created your source connection profile.
    • From the Source type menu, select the PostgreSQL profile type.
    • From the Destination type menu, select the BigQuery profile type.
  4. Review the required prerequisites that are generated automatically to reflect how your environment must be prepared for a stream. These prerequisites include how to configure the source database and how to configure BigQuery.

  5. Click CONTINUE. The Define PostgreSQL connection profile panel of the Create stream page appears.

Specify information about the source connection profile

  1. From the Source connection profile menu, select your source connection profile for PostgreSQL database.

  2. Click RUN TEST to verify that the source database and Datastream can communicate with each other.

    If the test fails, then the issue associated with the connection profile appears. Make the necessary changes to correct the issue, and then retest.

  3. Click CONTINUE. The Configure stream source panel of the Create stream page appears.

Configure information about the source database for the stream

  1. Provide the Replication slot and Publication names for your source database. The replication slot and publication were created when configuring your PostgreSQL database.

  2. Use the Objects to include menu to specify the tables and schemas in your source database that Datastream will replicate into BigQuery.

    For this quickstart, you want Datastream to transfer all tables and schemas. Therefore, select All tables from all schemas from the menu.

  3. Click CONTINUE. The Define BigQuery connection profile panel of the Create stream page appears.

Select a destination connection profile

  1. From the Destination connection profile menu, select your destination connection profile for BigQuery.

  2. Click CONTINUE. The Configure stream destination panel of the Create stream page appears.

Configure information about the destination for the stream

  1. Choose the Dataset for each schema option, so that Datastream automatically creates a dataset in BigQuery for every schema in the source database.

  2. Select the Location where the datasets will be created in BigQuery. This location doesn't have to be the same as the region where the Datastream stream is created.

  3. Set the Prefix to quickstart-. Datastream will add this string to the beginning of every dataset that it creates in BigQuery.

  4. Leave the value in the Specify the limit of data staleness drop-down list set to 15 minutes. BigQuery uses this value to decide how stale your data may be when queried.

  5. Click CONTINUE. The Review stream details and create panel of the Create stream page appears.

Create the stream

  1. Verify details about the stream as well as the source and destination connection profiles that the stream will use to transfer data from a source PostgreSQL database to BigQuery.

  2. Click RUN VALIDATION to validate the stream. By validating a stream, Datastream checks that the source is configured properly, validates that the stream can connect to both the source and the destination, and verifies the end-to-end configuration of the stream.

  3. After all validation checks pass, click CREATE.

  4. In the Create stream? dialog box, click CREATE.

Start the stream

In the previous section of the quickstart, you created a stream, but you didn't start it. You can do this now.

For this quickstart, you create and start a stream separately in case the stream creation process incurs an increased load on your source database. To put off that load, you create the stream without starting it, and then start the stream when the load can be incurred.

By starting the stream, Datastream can transfer data, schemas, and tables from the source database to the destination.

  1. Go to the Streams page for Datastream in the Google Cloud Console.

    Go to the Streams page

  2. Select the check box to the left of the stream that you want to start. For this quickstart, this is My Stream.

  3. Click START.

  4. In the dialog box, click START. The status of the stream changes from Not started to Starting to Running.

    After starting a stream, you can verify that Datastream transferred data from the source database to the destination.

Verify the stream

In this section, you confirm that Datastream transfers the data from all tables of your source PostgreSQL database into BigQuery.

  1. Go to the Streams page for Datastream in the Google Cloud Console.

    Go to the Streams page

  2. Click the stream that you created. For this quickstart, this is My Stream.

  3. In the Stream details page, click the link that appears below the Destination write path field. The BigQuery SQL Workspace opens in a separate tab.

  4. Verify that you see datasets and tables that represent schemas and tables of your source PostgreSQL database.

  5. Click one of the tables to see a preview of your data.

Clean up

To avoid incurring charges to your Google Cloud account for the resources used on this page, follow these steps.

  1. Use the Google Cloud console to delete your project, Datastream stream and connection profiles, and BigQuery datasets.

By cleaning up the resources that you created on Datastream, they won't take up quota and you won't be billed for them in the future. The following sections describe how to delete or turn off these resources.

Delete your project

The easiest way to eliminate billing is to delete the project that you created for this quickstart.

  1. In the Cloud console, go to the Manage resources page.

    Go to the Manage resources page

  2. In the project list, select the project that you want to delete, and then click Delete.

  3. In the dialog box, type the project ID, and then click Shut down to delete the project.

Delete the stream

  1. Go to the Streams page for Datastream in the Google Cloud Console.

    Go to the Streams page

  2. Click the stream that you want to delete. For this quickstart, this is My Stream.

  3. Click PAUSE.

  4. In the dialog box, click PAUSE.

  5. In the Stream status pane of the Stream details page, verify that the status of the stream is Paused.

  6. Click DELETE.

  7. In the dialog box, enter Delete in the text field, and then click DELETE.

Delete the connection profiles

  1. Go to the Connection profiles page for Datastream in the Google Cloud Console.

    Go to the Connection profiles page

  2. Select the check box for each connection profile that you want to delete. For this quickstart, select the checkboxes for My Source Connection Profile and My Destination Connection Profile.

  3. Click DELETE.

  4. In the dialog box, click DELETE.

Delete your BigQuery datasets

  1. Go to the BigQuery SQL Workspace in the Google Cloud Console.

    Go to the SQL Workspace page

  2. Expand the project node where you created this quickstart.

  3. For each dataset that you want to delete, click the View actions menu and then click Delete.

  4. In the dialog box, enter delete in the text field, and then click DELETE.

What's next

  • Learn more about Datastream.
  • Try out other Google Cloud features for yourself. Have a look at our quickstarts.